fivbvis provides an R client to the FIVB VIS web service system.
Installation
You can install the development version of fivbvis like so:
install.packages("remotes") ## if needed
remotes::install_github("wehsLai/fivbvis")Example
This is a basic example which shows you how to get data:
By default, results are cached in a per-session cache, so if we make the same request again the local results are used, rather than re-downloading.
1. Tournaments List with Filter
library(fivbvis) # load package
pl <- list(Fields = "No ShortNameOrName Season DefaultPlayersRanking")
cl <- list(Filter = c(Seasons = "2021"))
vb_tournaments <- v_get_volley_tournament_list(parent = pl, children = cl)
vb_tournaments
#> # A tibble: 46 × 4
#> no shortNameOrName season defaultPlayersR…
#> <int> <chr> <int> <int>
#> 1 1182 Tokyo Olympic Games - Women's Tournament 2021 NA
#> 2 1183 Tokyo Olympic Games - Men's Tournament 2021 NA
#> 3 1216 FIVB VNL WOMEN 2021 187
#> 4 1217 FIVB VNL MEN 2021 188
#> 5 1225 M FISU 2021 2021 NA
#> 6 1226 W FISU 2021 2021 NA
#> 7 1227 Volleyball Games - Tokyo Challenge 2021 Women 2021 NA
#> 8 1228 Volleyball Games - Tokyo Challenge 2021 Men 2021 NA
#> 9 1230 FIVB Volleyball Challenger Cup - Men (Cancelle… 2021 NA
#> 10 1231 FIVB Volleyball Challenger Cup - Women (Cancel… 2021 NA
#> # … with 36 more rows2. Matches List with Filter
s_tournament <- vb_tournaments[vb_tournaments$shortNameOrName == "FIVB VNL MEN", ]
pl <- list(Fields = "DateTimeLocal PoolName, TeamAName TeamBName MatchResultText")
cl <- list(Filter = c(NoTournament = s_tournament$no))
v_get_volley_match_list(parent = pl, children = cl)
#> # A tibble: 124 × 4
#> dateTimeLocal teamAName teamBName matchResultText
#> <dttm> <chr> <chr> <chr>
#> 1 2021-05-28 10:00:00 France Bulgaria 3-0
#> 2 2021-05-28 12:00:00 Germany Australia 3-0
#> 3 2021-05-28 13:00:00 Japan Iran 3-0
#> 4 2021-05-28 15:00:00 Serbia Slovenia 3-1
#> 5 2021-05-28 16:00:00 Netherlands Russia 1-3
#> 6 2021-05-28 18:00:00 USA Canada 3-0
#> 7 2021-05-28 19:30:00 Poland Italy 3-0
#> 8 2021-05-28 21:00:00 Brazil Argentina 3-0
#> 9 2021-05-29 10:00:00 Germany France 2-3
#> 10 2021-05-29 12:00:00 Iran Russia 1-3
#> # … with 114 more rows3. Pools List with Filter
pl <- list(Fields = "Name RoundName")
cl <- list(Filter = c(NoTournament = s_tournament$no, ForRanking = NULL))
v_get_volley_pool_list(parent=pl, children = cl)
#> # A tibble: 9 × 2
#> name roundName
#> <chr> <chr>
#> 1 Week 1 Preliminary Round
#> 2 Week 2 Preliminary Round
#> 3 Week 3 Preliminary Round
#> 4 Week 4 Preliminary Round
#> 5 Week 5 Preliminary Round
#> 6 Round robin - Men Preliminary Round
#> 7 Semifinals Final Round
#> 8 Final 3-4 Final Round
#> 9 Final 1-2 Final Round4. Teams List with Filter
pl <- list(Fields = "Code Name")
cl <- list(Filter = c(NoTournament = s_tournament$no))
v_get_volley_team_list(parent = pl, children = cl)
#> # A tibble: 16 × 2
#> code name
#> <chr> <chr>
#> 1 ARG Argentina
#> 2 AUS Australia
#> 3 BRA Brazil
#> 4 BUL Bulgaria
#> 5 CAN Canada
#> 6 FRA France
#> 7 GER Germany
#> 8 IRI Iran
#> 9 ITA Italy
#> 10 JPN Japan
#> 11 NED Netherlands
#> 12 POL Poland
#> 13 RUS Russia
#> 14 SLO Slovenia
#> 15 SRB Serbia
#> 16 USA USA5. Players List with Filter
pl <- list(Fields = "Team NoShirt FirstNamePlayer LastNamePlayer Position")
cl <- list(Filter = c(NoTournament = s_tournament$no))
v_get_volley_player_list(parent = pl, children = cl)
#> # A tibble: 271 × 4
#> noShirt firstNamePlayer lastNamePlayer position
#> <int> <chr> <chr> <chr>
#> 1 8 Wallace De Souza OP
#> 2 5 Tatsuya Fukuzawa OH
#> 3 6 Mitja Gasparini OP
#> 4 9 Dejan Vincic S
#> 5 17 Tine Urnaut OH
#> 6 2 Alen Pajenk MB
#> 7 12 Grzegorz Lomacz S
#> 8 6 Bartosz Kurek OP
#> 9 13 Michal Kubiak OH
#> 10 8 Marcus Böhme MB
#> # … with 261 more rows6. Statistics List with Filter, Relation
pl <- list(Fields = "BlockPoint BlockFault BlockContinue BlockTotal",
SumBy = "Tournament")
cl <- list(Filter = c(NoTournaments = s_tournament$no, MatchesToUse="MatchesFinished"),
Relation = c(Name="Match", Fields="NoInTournament DateLocal TeamACode TeamBCode MatchResult"),
Relation = c(Name="Team", Fields="Code Name"),
Relation = c(Name="Player", Fields="TeamName FirstName LastName VolleyPosition"))
v_get_volley_statistic_list(parent = pl, children = cl)
#> # A tibble: 279 × 11
#> blockPoint blockFault blockContinue blockTotal match team.code team.name
#> <int> <int> <int> <int> <lgl> <chr> <chr>
#> 1 23 67 45 135 NA <NA> <NA>
#> 2 8 27 22 57 NA <NA> <NA>
#> 3 3 14 14 31 NA <NA> <NA>
#> 4 9 14 13 36 NA <NA> <NA>
#> 5 1 1 0 2 NA <NA> <NA>
#> 6 17 19 21 57 NA <NA> <NA>
#> 7 10 17 17 44 NA <NA> <NA>
#> 8 28 34 46 108 NA <NA> <NA>
#> 9 11 29 23 63 NA <NA> <NA>
#> 10 15 21 13 49 NA <NA> <NA>
#> # … with 269 more rows, and 4 more variables: player.teamName <chr>,
#> # player.firstName <chr>, player.lastName <chr>, player.volleyPosition <chr>7. Pool Ranking
pl <- list(Fields = "No")
cl <- list(Filter = c(NoTournament = s_tournament$no, ForRanking=TRUE))
vb_pools_frk <- v_get_volley_pool_list(parent=pl, children = cl)
if(length(vb_pools_frk) > 0) {
pl <- list(NoPool = vb_pools_frk$no[1],
Fields = "RankTextWithRepeat TeamCode MatchPoints MatchesWon MatchesLost Matches")
v_get_volley_pool_ranking(parent = pl)
}
#> # A tibble: 16 × 6
#> rankTextWithRepeat teamCode matchPoints matchesWon matchesLost matches
#> <int> <chr> <int> <int> <int> <int>
#> 1 1 BRA 38 13 2 15
#> 2 2 POL 37 12 3 15
#> 3 3 SLO 34 12 3 15
#> 4 4 FRA 34 11 4 15
#> 5 5 RUS 34 11 4 15
#> 6 6 SRB 28 10 5 15
#> 7 7 USA 24 8 7 15
#> 8 8 CAN 21 7 8 15
#> 9 9 ARG 20 7 8 15
#> 10 10 ITA 19 7 8 15
#> 11 11 JPN 19 7 8 15
#> 12 12 IRI 18 5 10 15
#> 13 13 GER 14 4 11 15
#> 14 14 NED 11 3 12 15
#> 15 15 BUL 7 2 13 15
#> 16 16 AUS 2 1 14 158. Tournament Ranking
pl <- list(NoTournament = s_tournament$no,
Fields = "RankTextWithRepeat TeamName")
v_get_volley_tournament_ranking(parent = pl)
#> # A tibble: 16 × 2
#> rankTextWithRepeat teamName
#> <int> <chr>
#> 1 1 Brazil
#> 2 2 Poland
#> 3 3 France
#> 4 4 Slovenia
#> 5 5 Russia
#> 6 6 Serbia
#> 7 7 USA
#> 8 8 Canada
#> 9 9 Argentina
#> 10 10 Italy
#> 11 11 Japan
#> 12 12 Iran
#> 13 13 Germany
#> 14 14 Netherlands
#> 15 15 Bulgaria
#> 16 16 Australia9. Player Spike Ranking
if(!is.na(s_tournament$defaultPlayersRanking)) {
pl <- list(No = s_tournament$defaultPlayersRanking,
NumberOfScorers = 10, NumberOfPlayers = 10, Skills = "Spike")
vb_players_ranking <- v_get_volley_player_ranking(parent = pl)
vb_players_ranking$Spike[c("TeamCode", "FirstName", "LastName", "Successes", "Faults", "Continues", "TotalAttempts", "Note")]
}
#> # A tibble: 10 × 8
#> TeamCode FirstName LastName Successes Faults Continues TotalAttempts Note
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 BRA Wallace De Souza 150 39 69 258 58.14
#> 2 IRI Meisam Salehi 138 44 68 250 55.20
#> 3 JPN Yuki Ishikawa 149 28 93 270 55.19
#> 4 NED Nimir Abdel-A… 218 77 113 408 53.43
#> 5 BRA Ricardo Luc… Souza 131 38 79 248 52.82
#> 6 SRB Marko Ivovic 158 35 111 304 51.97
#> 7 RUS Maxim Mikhayl… 167 45 111 323 51.70
#> 8 SRB Drazen Luburic 133 46 81 260 51.15
#> 9 BRA Yoandy Leal Hi… 139 39 94 272 51.10
#> 10 ITA Alessandro Michiel… 152 27 125 304 50.00Troubleshooting
Known issues:
internal error: Huge input lookup
This indicates that the XML response from the FIVB server is too large or deeply nested and is causing the parser to fail. By default the parser restricts the nesting level that it allows, in order to prevent crashes or other undesirable behaviour. But you can remove this restriction by:
v_options(huge_xml = TRUE)and then try your request again.
